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Digital Climatic Atlas of Texas - Texas Water Development Board

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<strong>Digital</strong> <strong>Climatic</strong> <strong>Atlas</strong> <strong>of</strong> <strong>Texas</strong><br />

Executive Summary<br />

A digital climatic atlas <strong>of</strong> <strong>Texas</strong> has been created that defines the climate in terms<br />

<strong>of</strong> major climatic parameters, precipitation, maximum and minimum temperatures and<br />

lake evaporation. Datasets from wide-ranging sources <strong>of</strong> varying quality and resolutions<br />

were processed and assembled to create this comprehensive dataset <strong>of</strong> monthly and<br />

annual decadal means both in gridded (4 km) and point format for 11 decades from 1890<br />

to 2000. The datasets used to develop these gridded and point decadal means went<br />

through a variety <strong>of</strong> QA/QC procedures, data homogenization and infilling techniques to<br />

create the best possible serially complete data for estimating long-term decadal means.<br />

The accuracy <strong>of</strong> gridded datasets <strong>of</strong> precipitation and temperature obtained from the<br />

PRISM database were assessed based on independent sets <strong>of</strong> observation from the <strong>Texas</strong><br />

High Plains ET network. Due to low station density and lack <strong>of</strong> long-term pan<br />

evaporation data, the aerodynamic method was used to create high resolution lake<br />

evaporation estimates based on the gridded weather parameters obtained from PRISM<br />

and subsequently adjusted based on the point observations. ArcGIS geodatabases<br />

containing gridded data and a database containing point monthly and annual decadal<br />

means <strong>of</strong> climatic parameters were developed to facilitate efficient transfer and use <strong>of</strong><br />

data. Further, using this high resolution spatial data, a schema has been proposed to<br />

classify <strong>Texas</strong> into climatic zones <strong>of</strong> varying size by using a statistical procedure. This<br />

high-resolution digital climatic dataset will be <strong>of</strong> immense use for large scale and local<br />

water resources planning and conservation projects in addition to analysis <strong>of</strong> extreme<br />

events such as droughts and floods.<br />

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